For example, to authenticate users of various systems, users' biometric information is acquired, and then it is determined whether the biometric information that matches the acquired biometric information has been pre-registered with and is found in a database. Here, the similarity search can be effectively performed because the biometric information to be acquired at the time of authentication rarely perfectly matches the biometric information acquired at the time of registration.
To express the similarity level for performing the similarity search, there is available a technique for converting the feature values of biometric information into a hash vector. The technique identifies, as similar biometric information, each of pieces of biometric information that have hash vectors of close hamming distances.
Conventional techniques have employed a hyper-plane to convert feature values into a hash vector. However, there is also available a technique for employing a hyper-sphere to convert feature values into a hash vector, and it is expected that the technique using the hyper-sphere implements an improvement in accuracy.